Resolution:
standard / ## Figure 2.
Linear regression evaluation result. It shows the RMSE (a) and the correlation (b) between the prediction values of the linear models (which are based on the cis-regulatory matrices) and the gene expression profiles. The three cis-regulatory element finding approaches are the naive model with simple k-mer counts (denoted by 'cis, simple ct'), our main model with both sequence information
and gene expression neighborhood information (denoted by 'cis, coexp'), and the reference
model developed by BrohÃ©e, et al., 2011 (denoted by 'ref [34]'). The fourth column shows the modeling result for the gene expressions by the original
input co-expression network of our method. The legend on the right of each bar chart
indicates the number of top k-mers used to build the linear model and predict the expression level (see Methods).
A lower RMSE or a higher correlation indicates a better prediction accuracy.
Gao |